text
stringlengths
0
1.16k
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
question: ['How many animals are in the image?'], responses:['2']
question: ['How many animals are in the image?'], responses:['1']
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
[('2', 0.12961991198727602), ('3', 0.12561270547489775), ('4', 0.12556127085987287), ('1', 0.1254920833223361), ('5', 0.12407835939022728), ('8', 0.124024076973589), ('7', 0.12288810153923228), ('29', 0.12272349045256851)]
[['2', '3', '4', '1', '5', '8', '7', '29']]
[('1', 0.12829009354978346), ('3', 0.12529928082343206), ('4', 0.12464806219229535), ('8', 0.12460015878893425), ('6', 0.12451220062887247), ('12', 0.124338487048427), ('2', 0.12420459433498025), ('47', 0.12410712263327517)]
[['1', '3', '4', '8', '6', '12', '2', '47']]
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
tensor([8.4535e-01, 1.5465e-01, 1.2792e-07, 8.4789e-10, 4.8460e-07, 9.4956e-07,
2.0663e-08, 5.4335e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>)
4 *************
['4', '5', '3', '8', '6', '1', '2', '11'] tensor([8.4535e-01, 1.5465e-01, 1.2792e-07, 8.4789e-10, 4.8460e-07, 9.4956e-07,
2.0663e-08, 5.4335e-09], device='cuda:0', grad_fn=<SelectBackward0>)
tensor([1.0000e+00, 7.0224e-09, 1.3595e-10, 6.4822e-08, 6.3850e-10, 1.2502e-09,
5.5448e-11, 3.9578e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 7.0224e-09, 1.3595e-10, 6.4822e-08, 6.3850e-10, 1.2502e-09,
5.5448e-11, 3.9578e-09], device='cuda:3', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(9.4956e-07, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:0', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=RIGHT,question='Is the dog in the image on the right outside?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.3595e-10, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1907e-07, device='cuda:3', grad_fn=<DivBackward0>)}
torch.Size([3, 3, 448, 448])
ANSWER0=VQA(image=RIGHT,question='How many animals are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([7, 3, 448, 448])
question: ['Is the dog in the image on the right outside?'], responses:['no']
[('no', 0.1313955057270409), ('yes', 0.12592208734904367), ('no smoking', 0.12472972590078177), ('gone', 0.12376514658020793), ('man', 0.12367833016285167), ('meow', 0.1235796378467502), ('kia', 0.12347643720898455), ('no clock', 0.12345312922433942)]
[['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock']]
torch.Size([3, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840
question: ['How many animals are in the image?'], responses:['1']
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839
[('1', 0.12829009354978346), ('3', 0.12529928082343206), ('4', 0.12464806219229535), ('8', 0.12460015878893425), ('6', 0.12451220062887247), ('12', 0.124338487048427), ('2', 0.12420459433498025), ('47', 0.12410712263327517)]
[['1', '3', '4', '8', '6', '12', '2', '47']]
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840
tensor([1.0000e+00, 3.4321e-08, 1.3666e-07, 4.6982e-11, 1.6725e-11, 3.4625e-09,
8.7430e-10, 1.7622e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>)
no *************
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 3.4321e-08, 1.3666e-07, 4.6982e-11, 1.6725e-11, 3.4625e-09,
8.7430e-10, 1.7622e-07], device='cuda:0', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(3.4321e-08, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.9802e-07, device='cuda:0', grad_fn=<DivBackward0>)}
tensor([1.0000e+00, 2.3824e-07, 3.5968e-08, 7.2658e-08, 1.0045e-09, 3.3718e-09,
6.0581e-09, 5.7683e-10], device='cuda:1', grad_fn=<SoftmaxBackward0>)
2 *************
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 2.3824e-07, 3.5968e-08, 7.2658e-08, 1.0045e-09, 3.3718e-09,
6.0581e-09, 5.7683e-10], device='cuda:1', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(3.5787e-07, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)}
tensor([1.0000e+00, 1.3517e-09, 2.5798e-10, 3.4904e-10, 2.3289e-10, 1.0795e-08,
7.4225e-09, 3.5050e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 1.3517e-09, 2.5798e-10, 3.4904e-10, 2.3289e-10, 1.0795e-08,
7.4225e-09, 3.5050e-10], device='cuda:2', grad_fn=<SelectBackward0>)
ANSWER0=VQA(image=LEFT,question='Are there clown fish in the image?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(2.0759e-08, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)}
torch.Size([7, 3, 448, 448])
ANSWER0=VQA(image=RIGHT,question='How many gorillas are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} >= 3')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([7, 3, 448, 448])
tensor([1.0000e+00, 5.2523e-10, 1.4026e-10, 2.4046e-10, 1.3383e-10, 2.6727e-08,
3.7910e-09, 6.6638e-10], device='cuda:3', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 5.2523e-10, 1.4026e-10, 2.4046e-10, 1.3383e-10, 2.6727e-08,
3.7910e-09, 6.6638e-10], device='cuda:3', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(3.7910e-09, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)}
question: ['Are there clown fish in the image?'], responses:['yes']
question: ['How many gorillas are in the image?'], responses:['4']
[('yes', 0.1298617250866936), ('congratulations', 0.12464161604141298), ('no', 0.12445222599225532), ('honey', 0.12437056445881921), ('solid', 0.12422595371654564), ('right', 0.12419889376311324), ('candle', 0.12414264780165109), ('chocolate', 0.12410637313950891)]
[['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate']]
[('4', 0.12804651361935848), ('5', 0.12521071898947128), ('3', 0.12515925906184908), ('8', 0.12489091845155219), ('6', 0.1245383468146311), ('1', 0.12441141527606933), ('2', 0.12403713327181662), ('11', 0.12370569451525179)]
[['4', '5', '3', '8', '6', '1', '2', '11']]
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
tensor([1.0000e+00, 2.1287e-09, 2.3589e-08, 2.9915e-08, 2.7505e-11, 7.6841e-11,
3.5908e-11, 5.6549e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.1287e-09, 2.3589e-08, 2.9915e-08, 2.7505e-11, 7.6841e-11,
3.5908e-11, 5.6549e-09], device='cuda:1', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), False: tensor(2.3589e-08, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(-2.3589e-08, device='cuda:1', grad_fn=<DivBackward0>)}
tensor([2.9604e-01, 7.0393e-01, 2.5655e-07, 4.2998e-09, 2.1162e-05, 3.0989e-09,
1.2710e-10, 1.4826e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>)
5 *************